Compositions and methods comprising biomarkers of sperm quality, semen quality and fertility

ABSTRACT

Provided are compositions and methods for determining or diagnosing abnormal sperm or fertility, comprising: obtaining sperm DNA from a test subject; determining the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, MEST, RNR1, CYP27B1 and ICAM1; and thereby determining or diagnosing abnormal sperm or fertility. Provided are compositions and methods for identifying agents that cause spermatogenic deficits or abnormal sperm fertility, comprising: obtaining human ES-cell derived primordial germ cells; contacting the germ cells or descendants thereof, with a test agent; culturing the contacted cells; determining, using a genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from the above group; and identifying at least one test agent that causes at least one of spermatogenic deficits, abnormal sperm, and abnormal fertility.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is claims the benefit of priority to U.S. Provisional Patent Application Ser. No. 60/985,170 filed 2 Nov. 2007, and incorporated by reference herein in its entirety.

FEDERAL FUNDING ACKNOWLEDGEMENT

This work was at least in part supported by the Southern California Environmental Health Sciences Center (grant # 5P30ES007048) funded by the National Institute of Environmental Health Sciences. The United States government therefore has certain rights in the invention.

FIELD OF THE INVENTION

Particular aspects relate generally to DNA methylation and epigenetic reprogramming during development and gametogenesis, and more particularly to novel and effective epigenetic biomarkers and methods for determining and/or diagnosis of sperm quality, semen quality and fertility, comprising determining the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, MEST, RNR1, CYP27B1 and ICAM1. Additional aspects relate to compositions and methods for identifying and/or screening for agents that cause spermatogenic deficits or abnormal sperm fertility, comprising contacting human (or murine, rat, Etc.) ES-cell derived primordial germ cells with a test agent and determining the methylation status of at least one CpG dinucleotide sequence from at least one sequence as disclosed herein.

BACKGROUND

Ten to twenty percent of couples attempting pregnancy are infertile. Male-factor infertility accounts entirely for approximately 20% of these cases, and is contributory in an additional 30% [1,2]. Well defined causes of male-factor infertility are known to include congenital and acquired dysfunction of the hypothalamic-pituitary-testicular endocrine axis, anatomic defects, chromosomal abnormalities, and point mutations [3-5]. However, these diagnoses account for only a small proportion of cases, and etiology remains unknown for most male-factor infertility patients [1,2].

The mammalian germ line undergoes extensive epigenetic reprogramming during development and gametogenesis. In males, dramatic chromatin remodeling occurs during spermatogenesis [6,7], and widespread erasure of DNA methylation followed by de novo DNA methylation occurs developmentally in two broad waves [6,8-11]. The first occurs before emergence of the germ line, establishing a pattern of somatic-like DNA hypermethylation in cells of the pre-implantation embryo that are destined to give rise to all cells of the body, including germ cells. The second widespread occurrence of erasure takes place uniquely in primordial germ cells. Subsequent de novo methylation occurs during germ cell maturation and spermatogenesis, establishing a male germ line pattern of DNA methylation that remains hypomethylated compared with somatic cell DNA [8,12-16].

A small number of studies have addressed the epigenetic state of the human male germ line. Substantial variation in DNA methylation profiles is reported in ejaculated sperm of young, apparently healthy men. Notable distinctions were observed both between samples from separate men and among individually assayed sperm from the same man [17].

Although this variation suggests that DNA methylation may be used as a biomarker of sperm quality, semen quality and fertility were not assessed in this study [17].

SUMMARY OF EXEMPLARY ASPECTS

Male-factor infertility is a common condition, and etiology is unknown for a high proportion of cases. Abnormal epigenetic programming of the germline is disclosed as a mechanism compromising spermatogenesis of some men currently diagnosed with idiopathic infertility. During germ cell maturation and gametogenesis, cells of the germ line undergo extensive epigenetic reprogramming. This process involves widespread erasure of somatic-like patterns of DNA methylation followed by establishment of sex-specific patterns by de novo DNA methylation.

According to particular aspects, incomplete reprogramming of the male germ line results in both altered sperm DNA methylation and compromised spermatogenesis.

Particular aspects provide the first discovery and disclosure ever of a broad epigenetic defect associated with abnormal semen parameters. Additional aspects relate to an underlying mechanism for these broad epigenetic changes, comprising improper erasure of DNA methylation during epigenetic reprogramming of the male germ line.

Concentration, motility and morphology of sperm was determined in semen samples collected by male members of couples attending an infertility clinic. METHYLIGHT™ and ILLUMINA™ assays were used to measure methylation of DNA isolated from purified sperm from the same samples. Methylation at numerous sequences was elevated in DNA from poor quality sperm, and provide novel and effective epigenetic biomarkers of sperm quality, semen quality and fertility.

Particular exemplary aspects, provide methods for determining or diagnosing abnormal sperm or fertility, comprising: obtaining a sample of human sperm DNA from a test subject; determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from the group consisting of HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, MEST, RNR1, CYP27B1 and ICAM1; and determining, based on the methylation status of the at least one CpG sequence, the presence or diagnosis of abnormal sperm or fertility with respect to the test subject. In certain aspects, the determined methylation status of the at least one CpG sequence is hypermethylation. In particular embodiments, determining the methylation status of at least one CpG dinucleotide sequence comprises treating the genomic DNA, or a fragment thereof, with one or more reagents to convert 5-position unmethylated cytosine bases to uracil or to another base that is detectably dissimilar to cytosine in terms of hybridization properties. Preferably, treating comprises use of bisulfite treatment of the DNA.

In certain aspects, the at least one gene sequence is selected from the group consisting of HRAS SEQ ID NOS:63 and 20, NTF3 SEQ ID NOS:2 and 14, MT1A SEQ ID NOS:4 and 16, PAX8 SEQ ID NOS:1 and 13, DIRAS3 SEQ ID NOS:3 and 15, PLAGL1 SEQ ID NOS:7 and 19, SFN SEQ ID NOS:6 and 18, SAT2CHRM1 SEQ ID NOS:9 and 21, MEST SEQ ID NOS:5 and 17, RNR1 SEQ ID NOS:10 and 22, CYP27B1 SEQ ID NOS:11 and 23 and ICAM1 SEQ ID NOS:12 and 24.

In particular aspects, abnormal sperm comprises at least one of abnormal sperm concentration, abnormal motility, abnormal total normal morphology, abnormal volume, and abnormal viscosity. In certain embodiments, abnormal sperm comprises at least one of abnormal sperm concentration, abnormal motility, and abnormal total normal morphology.

Certain aspects of the methods, comprise determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from the group consisting of HRAS, NTF3, MT1A, PAX8 and PLAGL1. In certain embodiments, the at least one gene sequence is selected from the group consisting of HRAS SEQ ID NOS:63 and 20, NTF3 SEQ ID NOS:2 and 14, MT1A SEQ ID NOS:4 and 16, PAX8 SEQ ID NOS:1 and 13, and PLAGL1 SEQ ID NOS:7 and 19.

Yet additional aspects, provide methods for determining or diagnosing abnormal sperm or fertility, comprising: obtaining a sample of human sperm DNA from a test subject; determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence from each of a repetitive DNA element sequence group, a maternally imprinted gene sequence group, and a non-imprinted gene sequence group; and determining, based on the methylation status of the at least one CpG sequence from each of the groups, the presence or diagnosis of abnormal sperm or fertility with respect to the test subject. In certain implementations, the at least one gene sequence from a repetitive element group comprises at least one selected from the group consisting of SAT2CHRM1 SEQ ID NOS:9 and 21. In certain aspects, the at least one gene sequence from a maternally imprinted gene group comprises at least one selected from the group consisting of PLAGL1 SEQ ID NOS:7 and 19, MEST SEQ ID NOS:5 and 17, and DIRAS3 SEQ ID NOS:3 and 15. In particular embodiments, the at least one gene sequence from a non-imprinted gene group comprises at least one selected from the group consisting of HRAS SEQ ID NOS:63 and 20, NTF3 SEQ ID NOS:2 and 14, MT1A SEQ ID NOS:4 and 16, PAX8 SEQ ID NOS:1 and 13, SFN SEQ ID NOS:6 and 18, RNR1 SEQ ID NOS:10 and 22, CYP27B1 SEQ ID NOS:11 and 23 and ICAM1 SEQ ID NOS:12 and 24.

Yet further aspects provide methods for screening for agents that cause spermatogenic deficits, abnormal sperm or abnormal fertility comprising: obtaining human ES-cell derived primordial germ cells; contacting the germ cells or descendants thereof, with at least one test agent; culturing the contacted germ cells or the descendants thereof under conditions suitable for germ cell proliferation or development; obtaining a sample of genomic DNA from the contacted cultured germ cells or the descendants thereof; determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from the group consisting of HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, MEST, RNR1, CYP27B1 and ICAM1; and identifying, based on the methylation status of the at least one CpG sequence, at least one test agent that causes at least one of spermatogenic deficits, abnormal sperm, and abnormal fertility. In certain aspects, the determined methylation status of the at least one CpG sequence is hypermethylation. In certain embodiments, the at least one gene sequence is selected from the group consisting of HRAS SEQ ID NOS:63 and 20, NTF3 SEQ ID NOS:2 and 14, MT1A SEQ ID NOS:4 and 16, PAX8 SEQ ID NOS:1 and 13, DIRAS3 SEQ ID NOS:3 and 15, PLAGL1 SEQ ID NOS:7 and 19, SFN SEQ ID NOS:6 and 18, SAT2CHRM1 SEQ ID NOS:9 and 21, MEST SEQ ID NOS:5 and 17, RNR1 SEQ ID NOS:10 and 22, CYP27B1 SEQ ID NOS:11 and 23 and ICAM1 SEQ ID NOS:12 and 24.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows, according to particular exemplary aspects, box plots illustrating associations between semen parameters and level of methylation (PMR) in DNA isolated from 65 study sperm samples. DNA methylation was measured by MethyLight. Methylation targets were sequences specific to the genes HRAS, NTF3, MT1A, PAX8, PLAGL1, DIRAS3, MEST and SFN and the repetitive element Satellite 2 (SAT2CHRM1). P-value for trend over category of semen parameter is given for each plot. Rows: DNA methylation targets; columns: semen parameters.

FIG. 2 shows, according to particular exemplary aspects, cluster analysis of 36 MethyLight targets in 65 study sperm DNA samples. Left: dendrogram defining clusters; rows: 35 methylation targets; columns: 65 study samples ordered left to right on sperm concentration (samples A-G were also included in Illumina analyses (see FIG. 3)) with poor to good concentration (blue), motility (purple), and morphology (green) represented by darkest to lightest hue; body of figure: standardized PMR values represented lowest to highest as yellow to red. X=missing.

FIG. 3 shows, according to particular exemplary aspects, Results of Illumina analysis of 1,421 autosomal sequences in DNA isolated from sperm and buffy coat. Seven study sperm samples (A-G; ordered left to right on sperm concentration), screening sperm (S), two buffy coat (1-2). Level of DNA methylation scored as β-value. Color: β-value for column sample at row sequence (green: βP<0.1; yellow: 0.1≦β≦0.25; orange 0.25<β≦0.5; red: β>0.5). Ml and PI: maternally and paternally imprinted genes (black bar). Sequences assigned to tertile of median β-value among buffy coat DNA samples (I, II, III) and sorted within tertile on median βP-value among sperm DNA samples. Box 1: sequences with sperm-specific DNA methylation; Box 2: sequences with buffy coat-specific DNA methylation.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

Overview. There have been several prior art attempts in the art to assess sperm DNA methylation together with either sperm quality or fertility outcomes. However, the measures of DNA methylation used were limited, consisting of either a nonspecific genome-wide measure [18], or small and specialized subsets of DNA methylation targets [19-21].

Specifically, in the only study prior art study addressing the relationship between DNA methylation and fertility outcomes, immunostaining was used to measure genome-wide levels of DNA methylation in samples of ejaculated sperm collected for conventional in vitro fertilization (IVF) [18], and no association was observed between sperm DNA methylation and either fertilization rate or embryo quality in 63 IVF cycles. There was, however, a possible association with pregnancy rate after transfer of good quality embryos. Interpretation of these results is limited by both small sample size and the use of a single summary measure of genome-wide DNA methylation.

Moreover, with respect to the prior art studies [19-21] with small and specialized subsets of DNA methylation targets, sequence-specific measures were used to investigate the relationship between methylation of human sperm DNA and spermatogenesis. One study assessed DNA from spermatogonia and spermatocytes microdissected from seminiferous tubules of biopsied testicular tissue with spermatogenic arrest. DNA profiles consistent with correctly established paternal imprints were reported in all samples [19]. In the remaining two studies [20 and 21], DNA profiles were measured at specific DMRs associated with each of two genes, one paternally and one materially imprinted, and the resulting profiles were related to concentration of ejaculated sperm, an indicator of sperm quality. One of these studies reported correctly erased maternal imprints and correctly established paternal imprints in DNA from sperm of low concentration [21]. By contrast, the second reported that although maternal imprinting of MEST was correctly erased in DNA from sperm of low concentration, methylation at an H19 sequence typically de novo methylated in spermatogenesis was incomplete in these samples [20]. No compelling explanation was offered for the apparently differing results of these studies. It is noteworthy, however, that each addressed sequences of only one or two imprinted genes, an extremely small and specialized subset of DNA methylation targets in the human genome. Data from these published studies could not, therefore, have revealed a disruption involving large numbers of genes, or shown that genes that are not imprinted are also affected.

Particular aspects provide methods for determining or diagnosing abnormal sperm or fertility, comprising: obtaining a sample of human sperm DNA from a test subject; determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from the group consisting of HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, MEST, RNR1, CYP27B1 and ICAM1; and determining, based on the methylation status of the at least one CpG sequence, the presence or diagnosis of abnormal sperm or fertility with respect to the test subject. In certain embodiments the at least one gene sequence is selected from the group consisting of HRAS SEQ ID NOS:63 and 20, NTF3 SEQ ID NOS:2 and 14, MT1A SEQ ID NOS:4 and 16, PAX8 SEQ ID NOS:1 and 13, DIRAS3 SEQ ID NOS:3 and 15, PLAGL1 SEQ ID NOS:7 and 19, SFN SEQ ID NOS:6 and 18, SAT2CHRM1 SEQ ID NOS:9 and 21, MEST SEQ ID NOS:5 and 17, RNR1 SEQ ID NOS:10 and 22, CYP27B1 SEQ ID NOS:11 and 23 and ICAM1 SEQ ID NOS:12 and 24.

In particular aspects at least on CpG dinucleotide sequence within an amplicon is determined. In preferred aspects, the at least one amplicon sequence is selected from the group consisting of: HRAS SEQ ID NOS:20, NTF3 SEQ ID NO: 14, MT1A SEQ ID NO:16, PAX8 SEQ ID NO:13, DIRAS3 SEQ ID NO:15, PLAGL1 SEQ ID NO:19, SFN SEQ ID NO:18, SAT2CHRM1 SEQ ID NO:21, MEST SEQ ID NO:17, RNR1 SEQ ID NO:22, CYP27B1 SEQ ID NO:23 and ICAM1 SEQ ID NO:24.

Preferably, the amplicon is part of a contiguous CpG island sequence. In preferred aspects, the CpG island sequence is selected from the group consisting of: HRAS SEQ ID NOS:63, NTF3 SEQ ID NO:2, MT1A SEQ ID NO:4, PAX8 SEQ ID NO:1, DIRAS3 SEQ ID NO:3, PLAGL1 SEQ ID NO:7, SFN SEQ ID NO:6, SAT2CHRM1 SEQ ID NO:9, MEST SEQ ID NO:5, RNR1 SEQ ID NO:10, CYP27B1 SEQ ID NO:11 and ICAM1 SEQ ID NO:12.

Coordinate methylation within CpG islands. According to particular aspects, and as recognized in the relevant art, hypermethylation is coordinate within a CpG island. For Example, data (see Eckhardt et al., Nat Genet. 2006 December; 38(12):1378-85. Epub 2006 Oct. 29; incorporated by reference herein in its entirety) has been generated by analyzing methylation (using bisulfite sequencing) in CG-rich regions across entire chromosomes to provide a methylation map of the human genome (at least of the CPG rich regions thereof). To date, these data comprise methylation data of 3 complete human chromosomes (22, 20, and 6) for a variety of different tissues and cell types. Based on these data, for methylation patterns within CpG dense regions, methylation is typically found to be either present for all methylatable cytosines or none. This methylation characteristic or pattern is referred to in the art as “co-methylation” or “coordinate methylation.” The findings of this paper support a “significant correlation” of comethylation over the distance of at least 1,000 nucleotides in each direction from a particular determined CpG within a CpG dense region (see, e.g., page 2, column 2, 1^(st) full paragraph, of Eckhardt et al publication document). Furthermore, such co-methylation forms the basis for long-standing common methods such as MSP and particular MethyLight embodiments that rely on such co-methylation (e.g., as employed herein, the primers and/or probes each typically encompass multiple CpG sequences), and has now been further confirmed over entire chromosomes by Eckhardt et al. Therefore, in view of the teachings of the present specification, there is a reasonable correlation between the claimed coordinately methylated sequences, and the recited methods and exemplary methylation marker sequences.

Measurement of DNA Methylation of the Genomic DNA of Spermatozoa at CpG Islands, DMRs of Imprinted Genes and Repetitive Elements

The present specification describes and discloses the first study ever to investigate the epigenetic state of abnormal human sperm using an extensive panel of DNA methylation assays. Abnormal epigenetic programming of the germ line is herein disclosed as a mechanism compromising fertility of particular men currently diagnosed with idiopathic infertility. Aspects of the present invention indicate that one or more epigenetic processes lead to abnormal spermatogenesis and compromised sperm function.

To assess sperm DNA, methylation at specific targets that are both more numerous and less specialized, a relatively large set of sequence-specific assays was selected for use in the presently disclosed studies and invention.

Specifically, DNA methylation was measured in ejaculated spermatozoa-interrogating sequences in repetitive elements, promoter CpG islands, and differentially methylated regions (DMRs) of imprinted genes. Then, to address the possible role of epigenetic programming in abnormal human spermatogenesis, sequence-specific levels of DNA methylation were related to standard measures of sperm quality.

Applicants' observations indicate a broad epigenetic abnormality of poor quality human sperm in which levels of DNA methylation are elevated at numerous sequences in several genomic contexts. Previous studies of DNA methylation in poor quality sperm interrogated only imprinted loci, measuring methylation of sequences in only one or two genes [19-21].

Aspects of the present invention provide, inter alia, compositions and methods having substantial utility for diagnosing or determining the presence of abnormal sperm or fertility (e.g., comprising at least one of abnormal sperm concentration, abnormal total normal morphology, abnormal motility, abnormal volume, and abnormal viscosity).

As described in the working Example 1, herein below, Applicants initially evaluated 294 MethyLight reactions for the presence of methylation in sperm DNA from an anonymous semen sample obtained from a sperm bank. Standard semen analysis was then conducted on samples collected by 69 men during clinical evaluation of couples with infertility. Thirty seven selected MethyLight reactions were used to assay sperm DNA from 65 of the study samples.

At many of the 37 sequences, methylation levels were elevated in DNA from poor quality sperm. For example, striking associations with each of sperm concentration, motility and morphology were observed for five sequences: HRAS, NTF3, MT1A, PAX8 and the maternally imprinted gene PLAGL1 (FIG. 1). Applicants also found elevated DNA methylation to be significantly associated with poor semen parameters for the DIRAS3 and MEST maternally imprinted genes (FIG. 1).

Associations between results of each of the 37 MethyLight assays and sperm concentration were highly significant for HRAS, NTF3, MT1A, PAX8, DIRAS3 and PLAGL1 and were also significant (somewhat less) for SFN, SAT2CHRM1 and MEST (see Table 1 of Example 1, and see also FIG. 1).

Unsupervised cluster analysis identified three distinct clusters of sequences based on DNA methylation profiles in the 65 samples (FIG. 2). The middle cluster shown in FIG. 2 includes eight of the above nine sequences (all except MT1A) individually associated with semen parameters, and includes not only three sequences that are differentially methylated on imprinted loci, but also three single copy sequences specific to non-imprinted genes, and a repetitive element, Satellite 2 (referred to herein as SAT2CHRM1).

Significantly, this surprising result indicates that sperm abnormalities may be associated with a broad epigenetic defect of elevated DNA methylation at numerous sequences of diverse types, rather than a defect of imprinting alone as previously suggested [20].

To learn more about the possible extent of this apparent defect, the ILLUMINA™ platform was used to conduct DNA methylation analysis of 1,421 sequences in autosomal loci (discussed in more detail under Example 1 herein below). Briefly, the results of the ILLUMINA™ analyses appear in FIG. 3. Box 1 of FIG. 3 identifies 19 sequences with sperm-specific DNA methylation.

Various semen parameters have been correlated herein with abnormal DNA methylation (sperm concentration; total normal morphology; motility, volume, viscosity, etc.). According to preferred aspects, three of these semen parameters show the highest correlations with abnormal DNA methylation: sperm concentration; total normal morphology; and motility. FIG. 2, for example, shows that the corresponding MLL reactions are clustered based on sperm concentration.

Particular aspects of the present invention, therefore, provide marker(s) and marker subsets having utility for determining at least one of (A) abnormal sperm concentration, (B) abnormal morphology, and (C) abnormal motility. With respect to (A), abnormal sperm concentration, markers are provided in the following order of statistical significance from left to right, based on the p-value: HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, MEST, RNR1, and CYP27B1. Nine of these markers have p-values well below 0.05, and therefore are very significant. Additionally provided are the markers, RNR1 and CYP27B1, both having p-values of 0.02, and therefore also provide for utility in this respect.

With respect to (B), abnormal total motile sperm, markers are provided in the following order of statistical significance from left to right, based on the p-value: HRAS, NTF3, MT1A (NTF3 and MT1A equally significant), SAT2CHRM1, DIRAS3, PLAGL1, MEST, PAX8, and SFN. These markers have p-values well below 0.05, and therefore are very significant. Additionally provided are the markers: RNR1 (p-value 0.04) and CYP27B1 and BDNF (both with p-value of 0.05), and therefore also provide for utility in this respect.

With respect to (C), abnormal motility, markers are provided in the following order of statistical significance from left to right, based on the p-value: MT A, MEST, NTF3, PLAGL1. Additionally provided are the markers PAX8 AND ICAM1 (both having p-values of 0.05), and therefore also provide for utility in this respect.

Improper Erasure of Pre-Existing Methylation

According to particular aspects, only sequence-specific measures of DNA methylation are expected to reveal variation at individual sites, because of the enormous number of methylation targets in the human genome. These include millions of repetitive DNA elements for which methylation is postulated to silence parasitic and transposable activity. There are also large numbers of target sequences corresponding to single copy genes. Examples include thousands of promoter CpG islands for which methylation appears to mediate expression of genes in a tissue- and lineage-specific fashion, and DMRs associated with dozens of imprinted genes for which parent-of-origin DNA methylation marks are believed to mediate monoallelic expression in somatic cells.

As disclosed herein, Applicants' high-throughput analysis addressed hundreds of DNA methylation targets, and was thus designed to reveal methylation defects.

Elevated DNA methylation could, in theory, arise from either de novo methylation or improper erasure of pre-existing methylation. Although Applicants cannot rule out the possibility that processes responsible for de novo methylation are inappropriately activated in abnormal spermatogenesis, according to particular aspects, disruption of erasure is most likely the primary mechanism underlying abnormal spermatogenesis. Widespread erasure of DNA methylation occurs in both the pre-implantation embryo and again, uniquely, in primordial germ cells around the time that they enter the genital ridge. Several factors point to disruption of the second erasure as underlying the defect(s) described herein. Primordial germ cells arise from cells of the proximal epiblast which have themselves embarked upon somatic development, as shown by expression of somatic genes [25,26]. The germ cell lineage must therefore suppress the somatic program, which in mice is accomplished in part by genome-wide erasure of DNA methylation soon after germ cells migrate to the genital ridge [27]. This erasure affects DNA methylation on single copy genes, imprinted genes and repetitive elements [27]. Therefore, disruption of the second, genital ridge erasure most likely results in the type of pattern we observe in poor quality sperm, with elevated levels of DNA methylation at DNA sequences of each of these sequence types. Further, because this second erasure is confined to primordial germ cells, Applicants further reasoned that its disruption would be compatible with normal somatic development.

In humans, primordial germ cells colonize the genital ridge at about 4.5 weeks of gestation. Applicants are not aware of data describing DNA methylation in the human germ line at this date; however, the DMR in MEST at which Applicants found elevated DNA methylation in poor quality sperm is reportedly unmethylated in the male germ line by week 24 of gestation [28]. Potential causes of disrupted erasure have not been investigated. However, weeks 4.5-24 of gestation represent post-implantation stages of development wherein fetal physiology may be influenced by maternal factors and environmental compounds that cross the placenta. Possible origins of male infertility as early as 4.5 weeks of human gestation have not been studied. However, transient in vivo chemical exposure at 7-15 days post conception, which includes the analogous stage of murine development [29,30], results in spermatogenic deficits in rats with grossly normal testes [31] and may be associated with elevated methylation of sperm DNA [32].

Taken together, the observations disclosed herein indicate for the first time that epigenetic mechanisms contribute to a substantial portion of male factor infertility, and provide novel compositions and methods for the diagnosis, detection or determination of abnormal sperm or fertility. Also provided are methods for screening for agents that cause spermatogenic deficits, abnormal sperm or fertility comprising: obtaining human ES-cell derived primordial germ cells; contacting the germ cells with at least one test agent; culturing the contacted germ cells; obtaining a sample of genomic DNA from the contacted cultured germ cells; determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from the group consisting of HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, MEST, RNR1, CYP27B1 and ICAM1; and identifying, based on the methylation status of the at least one CpG sequence, at least one test agent that causes spermatogenic deficits, abnormal sperm or fertility.

Example 1 Sequence-Specific Levels of DNA Methylation were Related to Standard Measures of Sperm Quality

Overview. This is the first study ever to describe the epigenetic state of abnormal human sperm using an extensive panel of DNA methylation assays. To assess sperm DNA methylation at specific targets that are both more numerous and less specialized, a relatively larger set of sequence-specific assays was selected for use in the present study. DNA methylation was measured in ejaculated spermatozoa-interrogating sequences in repetitive elements, promoter CpG islands, and differentially methylated regions (DMRs) of imprinted genes. Then, to address the possible role of epigenetic programming in abnormal human spermatogenesis, sequence-specific levels of DNA methylation were related to standard measures of sperm quality.

Materials and Methods

Semen samples. Study semen samples were collected by 69 consecutive men ages 22-49 years who were partners of women undergoing evaluation for infertility at the Endocrine/Infertility Clinic of the Los Angeles County/University of Southern California Keck School of Medicine Medical Center. One additional semen sample was obtained from a sperm bank. The study was approved by the Institutional Review Board of the University of Southern California. Informed consent was not required because this research involved stored materials that had previously been collected solely for non-research purposes and were anonymous to the researchers/authors.

Semen Analysis. Standard semen analysis was performed using WHO criteria and Strict Morphology as previously described [33,34]. Semen volume, sperm concentration and motility, and leukocyte count were measured using the MicroCell chamber (Conception Technologies, San Diego, Calif.). Sperm morphology was assessed with the use of prestained slides (TestSimplets, Spectrum Technologies, Healdsburgh, Calif.), and percentage of morphologically normal sperm was documented. The samples were categorized according to concentration (<5, 5-20, >20 million sperm/ml), motility (<10, 10-50, >50 total motile sperm count (×10⁶)), and morphology (<5%, 5-14%, >14% normal) of sperm [33,35]. Presence of any white blood cells, round cells, or epithelial cells was recorded. Following semen analysis, samples were stored at −30° C. until processing for molecular analysis.

Sperm Separation from Seminal Plasma. Semen samples were allowed to thaw at 37° C. Sperm were separated from seminal plasma using ISOLATE® Sperm Separation Medium (Irvine Scientific, Santa Ana, Calif.), a density gradient centrifugation column designed to separate cellular contaminants (including leukocytes, round cells, and miscellaneous debris) from spermatozoa [24]. Separation was performed according to the manufacturer's protocol [36], and the purity of separated sperm from contaminating cells was documented by light microscopy.

DNA isolation. DNA was isolated from purified sperm as previously described [37], with 0.1×SSC added to the Lysis buffer, and samples incubated at 55° C. over night or longer to complete the lysis procedure.

Laboratory Analysis of DNA Methylation. Sodium bisulfite conversion was performed as previously described [23]. The amount of DNA in each aliquot was normalized, and a bisulfite-dependent, DNA methylation-independent control reaction was performed to confirm relative amounts of DNA in each sample. METHYLIGHT™ analyses were performed as previously described [23]. Reaction IDs and sequences of the primers and probes used in the 294 METHYLIGHT™ reactions are as previously published (see Table S1 (Sections A-B): doi:10.1371/journal.pone.0001289.s001 (0.10 MB PDF; incorporated by reference herein in its entirety). Additionally, according to particular aspects of the present invention, names of preferred markers and respective primers, probes and genomic sequences corresponding to the respective amplicons are listed below in TABLE 1.

TABLE 1 Primers and Probes for exemplary preferred MethyLight Assays. Genomic sequence Forward Reverse Probe Oligo corresponding to Primer Primer Sequence amplicon Sequence Gene (SEQ ID NO:) (SEQ ID NO:) (SEQ ID NO:) (SEQ ID NO:) HRAS GAGCGATGACG CGTCCACAAAA 6FAM- CGTCCACAAAATGGTTCTGG GAATATAAGTT TAATTCTAAAT CACTCTTACCC ATCAGCTGGATGGTCAGCGC GG CAACTAA ACACCGCCGAC ACTCTTGCCCACACCGCCGG (SEQ ID (SEQ ID G-BHQ-1 CGCCCACCACCACCAGCTTA NO: 46) NO: 47) (SEQ ID TATTCCGTCATCGCTC NO: 48) (SEQ ID NO: 20) NTF3 TTTCGTTTTTG CCGTTTCCGCC 6FAM- CCCCGCCCTTGTATCTCATG TATTTTATGGA GTAATATTC TCGCCACCACG GAGGATTACGTGGGCAGCCC GGATT (SEQ ID AAACTACCCAC CGTGGTGGCGAACAGAACAT (SEQ ID NO: 29) G-BHQ-1 CACGGCGGAAACGG NO: 28) (SEQ ID (SEQ ID NO: 14) NO: 30) MT1A CGTGTTTTCGT CTCGCTATCGC 6FAM- CGTGTTCCCGTGTTACTGTG GTTATTGTGTA CTTACCTATCC TCCACACCTAA TACGGAGTAGTGGGTCCGAG CG (SEQ ID ATCCCTCGAAC GGACCTAGGTGTGGACAGGG (SEQ ID NO: 35) CCACT-BHQ-1 ACAGGCAAGGCGACAGCGAG NO: 34) (SEQ ID (SEQ ID NO: 16) NO: 36) PAX8 CGGGATTTTTT ACCTTTCCCCA 6 FAM- CGGGACCTCCCTGTCGTACC TGTCGTATTTG TACTACCTCCG ACGAACAATTC TGAGAGGAGGGCCTGGCCCG A (SEQ ID ACGAACCAAAC TGAACTGCCCGTACACGGAG (SEQ ID NO: 26) CCTCCT-BHQ-1 GCAGCATGGGGAAAGGC NO: 25) (SEQ ID (SEQ ID NO: 13) NO: 27) DIRAS3 GCGTAAGCGGA CCGCGATTTTA 6 FAM- GCGCAAGCGGAATCTATGCC ATTTATGTTTGT TATTCCGACTT CGCACAAAAAC TGTTACCCACACTCCCTGCG (SEQ ID (SEQ ID GAAATACGAAA CCCCCGCACCCCGCTCCTGT NO: 31) NO: 32) ACGCAAA- GCGCAAGTCGGAATATAAAA BHQ-1 CCGCGG (SEQ ID (SEQ ID NO: 15) NO: 33) PLAGL1 ATCGACGGGTT CTCGACGCAAC 6FAM- ACCGACGGGCTGAATGACAA GAATGATAAATG CATCCTCTT ACTACCGCGAA ATGGCAGATGCCGTGGGCTT (SEQ ID (SEQ ID CGACAAAACCC TGCCGCCCGCGGCAGCCAAG NO: 43) NO: 44) ACG-BHQ-1 AGGATGGCTGCGCCGAG (SEQ ID (SEQ ID NO: 19) NO: 45) SFN GAGGAGGGTTC ATCGCACACGC 6FAM- GAGGAGGGCTCGGAGGAGAA GGAGGAGAA CCTAAAACT TCTCCCGATAC GGGGCCCGAGGTGCGTGAGT (SEQ ID (SEQ ID TCACGCACCTC ACCGGGAGAAGGTGGAGACT NO: 40) NO: 41) GAA-BHQ-1 GAGCTCCAGGGCGTGTGCGA (SEQ ID C NO: 42) (SEQ ID NO: 18) SAT2CHR TCGAATGGAAT CCATTCGAATC 6FAM- TCGAATGGAATCAACATCCA M1 TAATATTTAAC CATTCGATAAT CGATTCCATTC ACGGAAAAAAACGGAATTAT GGAAAA TCT GATAATTCCGT CGAATGGAATCGAAGAGAAT (SEQ ID (SEQ ID TT-MGBNFQ CATCGAATGGACCCGAATGG NO: 49) NO: 50) (SEQ ID (SEQ ID NO: 21) NO: 51) MEST CGGCGTTCGGT CACACTCACCT 6 FAM- CGGCGCCCGGTGCTCTGCAA GTTTTGTAA ACGAAAACGAT ACGCACCATAA CGCTGCGGCGGGCGGCATGG (SEQ ID CTC CCGCGTTATCC GATAACGCGGCCATGGTGCG NO: 37) (SEQ ID CATACC-BHQ-1 CCGAGATCGCCTCCGCAGGT NO: 38) (SEQ ID GAGTGTG NO: 39) (SEQ ID NO: 17) RNR1 CGTTTTGGAGA AAACAACGCCG 6 FAM- CGCTCTGGAGACACGGGCCG TACGGGTCG AACCGAA ACCGCCCGTAC GCCCCCTGCGTGTGGCACGG (SEQ ID (SEQ ID CACACGCAAA- GCGGCCGGGAGGGCGTCCCC NO: 52) NO: 53) BHQ-1 GGCCCGGCGCTGCTC (SEQ ID (SEQ ID NO:22) NO: 54) CYP27B1 GGGATAGTTAG CCGAATATAAC 6FAM- GGGACAGCCAGAGAGAACGG AGAGAACGGAT CACACCGCC CCAACCTCAAC ATGCCCATGAAATAAGGAAA GTTT (SEQ ID TCGCCTTTTCC AGGCGAGTTGAGGCTGGGGG (SEQ ID NO: 56) TTATTTCA- CGGTGTGGCTACACTCGG NO: 55) BHQ-1 (SEQ ID NO: 23) (SEQ ID NO: 57) ICAM1 GGTTAGCGAGG TCCCCTCCGAA 6 FAM- GGCCAGCGAGGGAGGATGAC GAGGATGATT ACAAATACTAC TTCCGAACTAA CCTCTCGGCCCGGGCACCCT (SEQ ID AA CAAAATACCCG GTCAGTCCGGAAATAACTGC NO: 58) (SEQ ID AACCGAAA- AGCATTTGTTCCGGAGGGGA NO: 59) BHQ-1 (SEQ ID NO: 24) (SEQ ID NO: 60)

Thirty-five METHYLIGHT™ reactions were selected for analysis of study sperm DNA samples based on cycle threshold (C(t)) values from analysis of the anonymous sample of sperm DNA. In brief, C(t) value is the PCR cycle number at which the emitted fluorescence is detectable above background levels. The C(t) value is inversely proportional to the amount of each methylated locus in the PCR reaction well, such that a low C(t) value suggests that the interrogated sequence is highly methylated. C(t) values of 35 or less were interpreted as an indication that a given sequence was methylated in the anonymous sample and selected 33 reactions on this basis. Three additional reactions were included, for which C(t) values slightly exceeded 35. Two (CYP27B1 and HOXA10) were selected based on gene function potentially related to fertility, and one (a non-CpG island reaction for IFNG) based on prior observation by applicants of hypomethylation in tumor versus normal tissue. When multiple reactions for a single locus resulted in C(t) values of less than 35, we selected only the reaction with the lowest C(t) value. Results of METHYLIGHT™ analysis were scored as PMR values as previously defined [23]. Following METHYLIGHT™ analyses, DNA remained from a subset of abnormal samples with greater sperm concentration. ILLUMINA™ analysis was performed on sodium bisulfite-converted sperm DNA of selected remaining samples, the anonymous semen sample, and purchased buffy coat DNA (HemaCare® Corporation, Van Nuys, Calif.) at the USC Genomics Core. Sodium bisulfite conversion for ILLUMINA™ assay was performed using the EZ-96 DNA Methylation Kit™ (ZYMO Research) according to manufacturer's protocol. Illumina Methods and reagents are as previously described [38]. The primer names and probe IDs are listed as previously published (see Table S2; doi:10.1371/journal.pone.0001289.s002 (0.20 MB PDF; incorporated by reference herein in its entirety), identifying 1,421 autosomal sequences of the GoldenGate Methylation Cancer Panel 1, more fully described elsewhere [39,40]. Results of ILLUMINA™ assays were scored as β-values [38]. Relevant amplicons and CpG islands are provided below in TABLE 2 below.

Statistical association analyses of METHYLIGHT™ data. Associations between the ranked METHYLIGHT™ data and categorized semen values (Table 1) were tested using simple linear regression, with the semen characteristic categories scored as 0: low, 1: mid, 2: high. For selected sequences, boxplots of the methylation values (on the log(PMR+1) scale) are shown in FIG. 1. The top and bottom of the box denote the 75^(th) and 25^(th) percentiles, and the white bar the median. Whiskers are drawn to the observation farthest from the box that lies within 1.5 times the distance from the top to the bottom of the box, with values falling outside the whiskers denoted as lines. Results of this analysis were included in FIG. 1 for sequences associated with sperm concentration using the Benjamini and Hochberg procedure [41] to control the false discovery rate at 5%.

TABLE 2 Exemplary, preferred amplicons and CpG islands Reaction HUGO Gene Previously Source of UniGene Reaction Alternate Gene Number Nomenclature Published? published reaction Number ID Name HB-144 HRAS Yes Widschwendter, M. Hs.37003 H-HRAS-M1B V-Ha-ras Harvey rat et al Cancer Res sarcoma viral 64, 3807-3813 (2004) oncogene homolog (HRAS); HRAS 1 HB-251 NTF3 Yes Weisenberger, D. J. Hs.99171 H-NTF3-M1B Neurotrophin 3 et al Nature Genet 38, 787-793 (2006). HB-205 MT1A Yes Weisenberger, D. J. Hs.655199 H-MT1A-M1B Metallothionein et al Nature Genet 1A/Metallothionein-I 38, 787-793 (2006). HB-212 PAX8 No Hs.469728 H-PAX8-M3B Paired Box Gene 8/ PAX8, Paired Domain Gene 8, PPARG Fusion Gene HB-043 DIRAS3 Yes Fiegl, H. et al Hs.194695 H-DIRAS3-M1B Ras homolog gene Cancer Epidemiol family, member BioMark Prev I/NOEY2; DIRAS 13, 882-888 (2004) family, GTP-binding RAS-like 3 (ARHI) HB-199 PLAGL1 Yes Weisenberger, D. J. Hs.444975 H-PLAGL1-M1B Pleiomorphic et al Nature Genet adenoma gene-like 38, 787-793 (2006). 1/LOT1/Zac1 HB-174 SFN Yes Weisenberger, D. J. Hs.523718 H-SFN-M1B Stratifin/14-3-3 et al Nature Genet protein sigma 38, 787-793 (2006). HB-289 SAT2CHRM1 Yes Weisenberger, D. J. N/A H-SAT2CHRM1-M1M SATELLITE 2 et al Nucleic Acids CHROMOSOME 1 Res 33, 6823-6836 (2005) HB-493 MEST No Hs.270978 H-MEST-M2B PEG1 HB-071 RNR1 Yes Muller, H. M. et al. N/A H-RNR1-M1B Ribosomal RNA Cancer Lett209, 231-236 (2004) HB-076 ICAM1 Yes Ehrlich, M. et al. Hs.643447 H-ICAM1B-M1B Intercellular Oncogene 21, adhesion molecule 1 6694-6702 (2002) (CD54), human rhinovirus receptor HB-223 CYP27B1 Yes Weisenberger, D. J. Hs.524528 H-CYB27B1-M1B cytochrome P450, et al Nature Genet family 27, subfamily 38, 787-793 (2006). B, polypeptide 1 GenBank mRNA Transcription Reaction HUGO Gene Chromosomal Accession accession Parallel/ Length of Start (GenBank Number Nomenclature Location Number number Antiparallel Sequence (bp) Numbering) HB-144 HRAS 11p15.5 AC137894 NM_176795 Antiparallel 165000 157238 HB-251 NTF3 12p13 AC135585 NM_002527 Parallel 35700 7048 HB-205 MT1A 16q13 AC106779 NM_005946 Parallel 158297 18787 HB-212 PAX8 2q12 AC016683 S77905 Antiparallel 179937 116171 HB-043 DIRAS3 1p31 AF202543 U96750 Parallel 7242 2053 HB-199 PLAGL1 6q24-q25 AL109755 U72621 Antiparallel 89669 53085 HB-174 SFN 1p35.3 AF029081 BC023552 Parallel 10034 8563 HB-289 SAT2CHRM1 1 X72623 N/A Parallel 1352 N/A HB-493 MEST 7q32.2 NC_000007 NM_177524 Parallel 20084 5893 HB-071 RNR1 13p12 X01547 N/A Parallel 850 482 HB-076 ICAM1 19p13.3- AC011511 BC015969 Parallel 156503 85732 p13.2 HB-223 CYP27B1 12q14.1 AY288916 AB005038 Parallel 7587 1324 Amplicon Start Amplicon End Mean Location Relative Location Relative Distance from Amplicon Amplicon to Transcription to Transcription Transcription Reaction HUGO Gene Location Start Location End Start (bp, Start (bp, Start (bp, Number Nomenclature (GenBank Numbering) (GenBank Numbering) GenBank sequence) GenBank Sequence) GenBank sequence) HB-144 HRAS 156015 155920 1223 1318 1271 HB-251 NTF3 7503 7576 455 528 492 HB-205 MT1A 18175 18254 −612 −533 −573 HB-212 PAX8 72708 72632 43463 43539 43501 HB-043 DIRAS3 1953 2038 −100 −15 −58 HB-199 PLAGL1 53045 52969 40 116 78 HB-174 SFN 8848 8928 285 365 325 HB-289 SAT2CHRM1 1074 1153 N/A N/A N/A HB-493 MEST 6057 6144 164 251 207 HB-071 RNR1 219 293 −263 −189 −226 HB-076 ICAM1 85597 85676 −135 −56 −96 HB-223 CYP27B1 1728 1805 404 481 443 Amplicon Amplicon UCSC UCSC Location of Reaction HUGO Gene Location Start Location End Strand Assembly Amplicon in Gene Number Nomenclature (UCSC Numbering) (UCSC Numbering) (+/−) Date (e.g., promoter, exon) HB-144 HRAS 524232 524327 + May 2004 Exon2 HB-251 NTF3 5473982 5474055 + May 2004 Exon1 HB-205 MT1A 55229471 55229550 + May 2004 Promoter HB-212 PAX8 113709183 113709259 + May 2004 Exon 9 HB-043 DIRAS3 68228349 68228434 − May 2004 Promoter (in Exon3) HB-199 PLAGL1 1443711135 144371211 + May 2004 Exon1 HB-174 SFN 26874056 26874136 + May 2004 Exon1 HB-289 SAT2CHRM1 no perfect no perfect May 2004 N/A match match HB-493 MEST 129919339 129919425 + March 2006 exon1/intron1 HB-071 RNR1 N/A N/A May 2004 Promoter HB-076 ICAM1 10242630 10242709 + May 2004 Promoter HB-223 CYP27B1 56446731 56446808 − May 2004 Exon1 500 (approx. ± Estimated CpG Island Location of Location of 250) bp sequence CpG Length (GenBank) CpG Island CpG Island Reaction HUGO Gene comprising amplicon Island (SEQ ID NO:) Start (GenBank End (GenBank Number Nomenclature (Genbank sequence) yes/no (>0.6 CpG:GpC) numbering) numbering) HB-144 HRAS 155726-156225 (Yes) 3354 (SEQ ID NO: 63) 156171 159524 HB-251 NTF3 7301-7800 Yes 609 (SEQ ID NO: 2) 7246 7854 HB-205 MT1A 18201-18700 Yes 1209 (SEQ ID NO: 4) 17842 19050 HB-212 PAX8 72426-72925 Yes 1250 (SEQ ID NO: 1) 73859 72610 HB-043 DIRAS3 1751-2250 Yes 552 (SEQ ID NO: 3) 1804 2355 HB-199 PLAGL1 52751-53250 Yes 1478 (SEQ ID NO: 7) 53667 52190 HB-174 SFN 8637-9136 Yes 661 (SEQ ID NO: 6) 8684 9344 HB-289 SAT2CHRM1  851-1350 (Yes) (500 (SEQ ID NO: 9)) N/A N/A HB-493 MEST Yes 2799 (SEQ ID NO: 5) 4293 7091 HB-071 RNR1  1-500 yes 850 (SEQ ID NO: 10) 1 850 HB-076 ICAM1 85376-85875 Yes 2038 (SEQ ID NO: 12) 84047 86084 HB-223 CYP27B1 1501-2000 yes 747 (SEQ ID NO: 11) 1345 2091 Reaction HUGO Gene Amplicon Start relative Reaction Bisulfite Conversion: Number Nomenclature to CGI start Type Top/Bottom Strand HB-144 HRAS N/A Methylated Bottom HB-251 NTF3 257 Methylated Top HB-205 MT1A 333 Methylated Top HB-212 PAX8 1151 Methylated Top HB-043 DIRAS3 149 Methylated Top HB-199 PLAGL1 622 Methylated Top HB-174 SFN 116 Methylated Top HB-289 SAT2CHRM1 N/A Methylated Top HB-493 MEST 1764 Methylated Top HB-071 RNR1 219 Methylated Top HB-076 ICAM1 1685 Methylated Top HB-223 CYP27B1 383 Methylated Top

Statistical cluster analysis of METHYLIGHT™ data. Hierarchical cluster analysis of 36 loci was performed, using correlation to measure the distance between any two loci and Ward's method of linkage [42]. SASH1 was omitted from the cluster analysis because only a single sample showed positive methylation. The 65 study samples were ordered from left to right by increasing semen concentration.

Display of ILLUMINA™ data. ILLUMINA™ data were displayed graphically in FIG. 3 with results for study samples ordered left to right in columns by sperm concentration. Rows corresponding to each of the 1,421 sequences were divided into three tertiles of median β-value among buffy coat DNA samples (I, II, III), then sorted within tertile by median β-value among all sperm DNA samples. Box 1 contains all sequences tertile I with median β-value among sperm DNA samples >0.5; box 2 contains all sequences within tertile III with median β-value among sperm DNA samples <0.1. Maternal or paternal imprinting status of each locus was scored according to the categorization of R. Jirtle [43]. All sequences specific to genes imprinted in humans were individually reviewed to determine whether they have been reported as belonging to a DMR for which parent of origin marks are maintained by DNA methylation [44-66]. Sequences meeting these criteria were scored as maternally imprinted (MI) or paternally imprinted (PI) with an indicator set for each on FIG. 3.

Results

Standard semen analysis was conducted on samples collected by 69 men during clinical evaluation of couples with infertility. Among the 69 samples, semen volume ranged from 0.5 to 7.8 ml; total count 0 to 864 million sperm; total motile count 0 to 396.3 million sperm; and percentage normal sperm forms 0 to 26%. Four samples were found to be azoospermic and excluded from subsequent analysis of DNA methylation.

Applicants evaluated 294 METHYLIGHT™ reactions for the presence of methylation in sperm DNA from an anonymous semen sample obtained from a sperm bank. Primers and probes were as previously published (see Table S1 (Sections A-B), found at doi:10.1371/journal.pone.0001289.s001 (0.10 MB PDF); incorporated by reference herein in its entirety; Primers, probes and reaction IDs for 294 MethyLight Assays: Group A, used in screening procedure and analysis of 65 study samples; Group B, used only in screening procedure; and Group C, new assays designed to DMRs of maternally imprinted genes and used only in analysis of 65 study samples.

The 35 selected reactions of Table S1A were used to assay sperm DNA from 65 study samples.

At many of the 35 sequences methylation levels were elevated in DNA from poor quality sperm. For example, striking associations with each of sperm concentration, motility and morphology were observed for five sequences: HRAS, NTF3, MT1A, PAX8 and PLAGL1 (FIG. 1).

PLAGL1 is maternally imprinted. Our METHYLIGHT™ assay for this gene interrogates a differentially methylated CpG island [22]. To determine whether other maternally imprinted genes are methylated in abnormal sperm, METHYLIGHT™ was used to interrogate the differentially methylated sequence of DIRAS3. At this sequence greater DNA methylation was also observed in samples with poorer semen parameters (FIG. 1, row 6). These results appeared to conflict with those of Marques et al [20] who reported no association between low sperm count and methylation of a DMR in a third maternally imprinted gene, MEST. We therefore used METHYLIGHT™ to assess the methylation status of a differentially methylated MEST sequence investigated by these authors [20], and found elevated DNA methylation to be significantly associated with poor semen parameters (FIG. 1), in agreement with our PLAGL1 and DIRAS3 results.

After correction for multiple comparisons, estimated associations between results of each of the 37 METHYLIGHT™ assays and sperm concentration were highly significant for HRAS, NTF3, MT1A, PAX8, DIRAS3 and PLAGL1 and marginally significant for SFN, SAT2CHRM1 and MEST (Table 3, FIG. 1).

TABLE 3 Trend p-values for associations between MethyLight results and semen parameters (see Methods). Parameter of Standard Semen Analysis MethyLight Reaction Concentration Motility Morphology *HRAS.HB.144 0.00006 0.00001 0.06265 *NTF3.HB.251 0.00029 0.00026 0.00464 MT1A.HB.205 0.00048 0.00026 0.00119 *PAX.8.HB.212 0.00086 0.00405 0.05143 *DIRAS3.HB.043 0.00109 0.00159 0.06016 *PLAGL1.HB.199 0.00213 0.00255 0.01951 *SFN.HB.174 0.00307 0.00804 0.79899 *SAT2CHRM1.HB.289 0.00448 0.00109 0.06793 *MEST.HB.493 0.00711 0.00373 0.00359 RNR1.HB.071 0.02 0.04 0.89 CYP27B1 0.02 0.05 0.10 MADH3.HB.053 0.09 0.15 0.35 BDNF.HB.257 0.11 0.05 0.26 PSEN1.HB.263 0.16 0.27 0.81 CGA.HB.237 0.23 0.34 0.93 SERPINB5.HB.208 0.23 0.64 0.80 ICAM1.HB.076 0.24 0.29 0.05 MINT1.HB.161 0.24 0.60 0.34 PTPN6.HB.273 0.24 0.09 0.08 ALU.HB.296 0.25 0.29 0.87 CYP1B1.HB.239 0.28 0.42 0.61 SP23.HB.301 0.28 0.48 0.48 IFNG.HB.311 0.33 0.22 0.93 C9.HB.403 0.37 0.35 0.89 GP2.HB.400 0.41 0.39 0.94 GATA4.HB.325 0.45 0.20 0.12 UIR.HB.189 0.48 0.47 0.70 TFF1.HB.244 0.48 0.96 0.93 LDLR.HB.219 0.51 0.39 0.11 SASH1.HB.085 0.51 0.15 0.15 ABCB1.HB.051 0.54 0.27 0.16 HOXA10.HB.270 0.63 0.84 0.13 MTHFR.HB.058 0.70 0.38 0.43 LINE1.HB.330 0.87 0.47 0.14 LZTS1.HB.200 0.90 0.95 0.73 SMUG1.HB.086 0.90 0.36 0.76 ^(‡)IGF2.HB.345 0.91 0.71 0.11 *Belongs to cluster 2 (see FIG. 2). ^(‡)Assay interrogates a non-differentially methylated sequence. Trends were assessed over the following categories of semen parameters: Concentration (<5, 5-20, >20 × 10⁶ sperm per ml), Morphology (<5%, 5-14%, >14% normal sperm forms), Motility (<10, 10-50, >50 total motile sperm count (×10⁶)).

Applicants then subjected METHYLIGHT™ data from 36 of the assays to unsupervised cluster analysis. (Data for SASH1 were not included, because methylation at this sequence was detected in only one sample.) This analysis identified three distinct clusters of sequences based on DNA methylation profiles in the 65 samples (FIG. 2). Notably, the middle cluster shown in FIG. 2 includes eight of the nine sequences (all except MT1A) individually associated with semen parameters. This middle cluster includes not only three sequences that are differentially methylated on imprinted loci, but also three single copy sequences specific to non-imprinted genes, and a repetitive element, Satellite 2 [23] (reaction named SAT2CHRM1).

Significantly, this surprising result indicates that sperm abnormalities may be associated with a broad epigenetic defect of elevated DNA methylation at numerous sequences of diverse types, rather than a defect of imprinting alone as previously suggested [20].

To learn more about the possible extent of this apparent defect, the ILLUMINA™ platform was used to conduct DNA methylation analysis of 1,421 sequences in autosomal loci. Included in this analysis was: DNA from the anonymous sperm sample used in the METHYLIGHT™ screen (FIG. 3, columns S); two purchased samples of buffy coat DNA allowing for observation of methylation patterns in somatic cells (FIG. 3, columns 1-2), and seven study sperm DNA samples remaining after METHYLIGHT™ analysis (FIGS. 2-3, columns A-G).

Results of ILLUMINA™ analyses appear in FIG. 3. A large number of genes were similarly methylated in both sperm DNA and buffy coat DNA (blue regions on the left bar, I; red regions on the right bar, III), while others tended to be more methylated in DNA isolated from only one of these cell types. Boxes enclose sequences for which we observed particularly strong patterns of cell type-specific methylation. Box 1 identifies 19 sequences with sperm-specific DNA methylation. At these sequences, methylation profiles of all DNA from samples of study sperm (A-G) closely resemble those from the anonymous sperm sample and differ greatly from those of buffy coat DNA. Box 2 identifies 102 sequences with buffy coat-specific DNA methylation. This set is larger in number than the sperm-specific set, as expected, given that sperm DNA is reportedly hypomethylated compared with somatic cell DNA [14]. The buffy coat-specific set comprises 7.2% of the 1,421 sequences including the majority of DMRs associated with imprinted genes that are on the Illumina panel. At many buffy coat-specific sequences, DNA methylation was elevated in study sperm DNA, most notably in sample A that had been isolated from sperm with the lowest concentration among samples A-G. Methylation of sample A DNA is elevated (β>0.1) at 76 of the 102 sequences in box 2, including all 10 that are known DMRs associated with imprinted genes.

Several factors assure us that our observations did not arise from somatic cell contamination of separated sperm samples [21]. Somatic cells are far larger than sperm and readily identified by microscopic evaluation of semen samples. Even if somatic cells are present in the neat ejaculate, the ISOLATE® sperm separation technique is specifically designed to separate spermatozoa from somatic cells and miscellaneous debris [24]. Moreover, although microscopic evaluation of semen samples conducted before sperm separation identified white blood cells in five of the 65 neat semen samples, excluding results on these five samples from statistical analyses had minimal effect on associations between DNA methylation and semen parameters, and DNA from these samples were excluded from ILLUMINA™ assays.

Various semen parameters have been correlated with abnormal DNA methylation (sperm concentration; total normal morphology; motility, volume, viscosity, etc.). According to preferred aspects, three of these semen parameters show the highest correlations with abnormal DNA methylation: sperm concentration; total normal morphology; and motility. FIG. 2, for example, shows that the corresponding MLL reactions are clustered based on sperm concentration.

Particular preferred aspects, therefore, provide marker(s) and marker subsets having utility for determining at least one of abnormal sperm concentration, abnormal morphology, and abnormal motility.

In particular aspects, with respect to (A) abnormal sperm concentration, markers are provided in the following order of statistical significance from left to right, based on the p-value: HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, and MEST. All of these nine markers have p-values well below 0.05, and therefore, all nine are very significant. Additionally provided are two more markers, RNR1 and CYP27B1, both have p-value of 0.02, that are therefore also of utility in this respect.

In particular aspects, with respect to (B) abnormal total motile sperm, markers are provided in the following order of statistical significance from left to right, based on the p-value: HRAS, NTF3, MT1A (NTF3 and MT1A equally significant), SAT2CHRM1, DIRAS3, PLAGL1, MEST, PAX8, & SFN. Again, these have very significant p-values. Additionally provided are three more markers: RNR1 (p-value 0.04) and CYP27B1, BDNF, both with p-value of 0.05, that are therefore also of utility in this respect.

In particular aspects, with respect to (C) abnormal motility, markers are provided in the following order of statistical significance from left to right, based on the p-value: MT1A, MEST, NTF3, PLAGL1. Additionally, PAX8 AND ICAM1 both have p-values of 0.05, and are thus also of utility in this respect.

Example 2 Additional Aspects Provide Methods for Screening for Agents that Cause Spermatogenic Deficits, Abnormal Sperm or Abnormal Fertility Overview

As stated herein above, this is the first study ever to describe the epigenetic state of abnormal human sperm using an extensive panel of DNA methylation assays. According to additional aspects, Applicants data has provided novel methylation-based markers for abnormal human sperm and/or fertility.

As recognized in the art, transient in vivo chemical exposure at 7-15 days post conception, which includes the analogous stage of murine development [29,30], results in spermatogenic deficits in rats with grossly normal testes [31] but likely associated with elevated methylation of sperm DNA [32].

According to additional aspects, therefore, Applicants' data provides for methods for screening for agents that cause spermatogenic deficits, abnormal sperm or abnormal fertility. In particular aspects, ES-cell derived primordial germ cells are exposed to chemical test agents, followed by CpG methylation analysis as described and provided for herein, to allow for a high-throughput screening assay to test and identify agents that cause spermatogenic deficits, abnormal sperm or abnormal fertility. Culturing of embryonic stem (ES) cells to efficiently provide for primordial germ cells is known in the art. For example, human embryonic stem (ES) cells are propagated on mouse embryo fibroblast feeder cells as described (67). A multistep induction procedure incorporating several previously described protocols can be used to convert ES cells into primordial germ cells at high efficiency. For example, ES cells are treated with bone morphogenetic protein-2 for a brief 24 period in combination with activin and FGF-2 in chemically defined medium. After 24 hours the BMP-2 is removed and retinoic acid is added. As will be appreciated in the art, a range of doses of each factor may be employed in a matrix design over a variable time course to optimize the yield of c-kit positive/placental alkaline phosphatase positive cells. These cells are isolated by flow cytometry and subjected to Q-RTPCR to analyze for the presence of primordial germ cell and gonocyte specific genes such as VASA. According to particular aspects, up to 10% of the treated cells are vasa positive following optimal treatment. Primordial germ cells and gonocytes may also be isolated from embryonic and fetal gonads by the use of c-kit and placental alkaline phosphatase in combination with flow cytometry, following collagenase and Tryple Express™ digestion of the tissue.

Particular aspects, therefore, provide methods for screening for agents that cause spermatogenic deficits, abnormal sperm or abnormal fertility comprising: obtaining human ES-cell derived primordial germ cells; contacting the germ cells or descendants thereof, with at least one test agent; culturing the contacted germ cells or the descendants thereof under conditions suitable for germ cell proliferation or development; obtaining a sample of genomic DNA from the contacted cultured germ cells or the descendants thereof; determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from the group consisting of HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, MEST, RNR1, CYP27B1 and ICAM1; and identifying, based on the methylation status of the at least one CpG sequence, at least one test agent that causes at least one of spermatogenic deficits, abnormal sperm, and abnormal fertility. In certain embodiments, the determined methylation status of the at least one CpG sequence is hypermethylation. In preferred embodiments, the at least one gene sequence is selected from the group consisting of HRAS SEQ ID NOS:63 and 20, NTF3 SEQ ID NOS:2 and 14, MT1A SEQ ID NOS:4 and 16, PAX8 SEQ ID NOS:1 and 13, DIRAS3 SEQ ID NOS:3 and 15, PLAGL1 SEQ ID NOS:7 and 19, SFN SEQ ID NOS:6 and 18, SAT2CHRM1 SEQ ID NOS:9 and 21, MEST SEQ ID NOS:5 and 17, RNR1 SEQ ID NOS:10 and 22, CYP27B1 SEQ ID NOS:11 and 23 and ICAM1 SEQ ID NOS:12 and 24.

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1. A method for determining or diagnosing abnormal sperm or fertility, comprising: obtaining a sample of human sperm DNA from a test subject; determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from the group consisting of HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, MEST, RNR1, CYP27B1 and ICAM1; and determining, based on the methylation status of the at least one CpG sequence, the presence or diagnosis of abnormal sperm or fertility with respect to the test subject.
 2. The method of claim 1, wherein the determined methylation status of the at least one CpG sequence is hypermethylation.
 3. The method of claim 1, wherein determining the methylation status of at least one CpG dinucleotide sequence comprises treating the genomic DNA, or a fragment thereof, with one or more reagents to convert 5-position unmethylated cytosine bases to uracil or to another base that is detectably dissimilar to cytosine in terms of hybridization properties.
 4. The method of claim 3, wherein treating comprises use of bisulfite treatment of the DNA.
 5. The method of claim 1, wherein the at least one gene sequence is selected from the group consisting of HRAS SEQ ID NOS:63 and 20, NTF3 SEQ ID NOS:2 and 14, MT1A SEQ ID NOS:4 and 16, PAX8 SEQ ID NOS:1 and 13, DIRAS3 SEQ ID NOS:3 and 15, PLAGL1 SEQ ID NOS:7 and 19, SFN SEQ ID NOS:6 and 18, SAT2CHRM1 SEQ ID NOS:9 and 21, MEST SEQ ID NOS:5 and 17, RNR1 SEQ ID NOS:10 and 22, CYP27B1 SEQ ID NOS:11 and 23 and ICAM1 SEQ ID NOS:12 and
 24. 6. The method of claim 1, wherein abnormal sperm comprises at least one of abnormal sperm concentration, abnormal motility, abnormal total normal morphology, abnormal volume, and abnormal viscosity.
 7. The method of claim 6, wherein abnormal sperm comprises at least one of abnormal sperm concentration, abnormal motility, and abnormal total normal morphology.
 8. The method of claim 7, comprising determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from the group consisting of HRAS, NTF3, MT1A, PAX8 and PLAGL1.
 9. The method of claim 8, wherein the at least one gene sequence is selected from the group consisting of HRAS SEQ ID NOS:63 and 20, NTF3 SEQ ID NOS:2 and 14, MT1A SEQ ID NOS:4 and 16, PAX8 SEQ ID NOS:1 and 13, and PLAGL1 SEQ ID NOS:7 and
 19. 10. A method for determining or diagnosing abnormal sperm or fertility, comprising: obtaining a sample of human sperm DNA from a test subject; determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence from each of a repetitive DNA element sequence group, a maternally imprinted gene sequence group, and a non-imprinted gene sequence group; and determining, based on the methylation status of the at least one CpG sequence from each of the groups, the presence or diagnosis of abnormal sperm or fertility with respect to the test subject.
 11. The method of claim 10, wherein the determined methylation status of the at least one CpG sequence is hypermethylation.
 12. The method of claim 10, wherein determining the methylation status of at least one CpG dinucleotide sequence comprises treating the genomic DNA, or a fragment thereof, with one or more reagents to convert 5-position unmethylated cytosine bases to uracil or to another base that is detectably dissimilar to cytosine in terms of hybridization properties.
 13. The method of claim 12, wherein treating comprises use of bisulfite treatment of the DNA.
 14. The method of claim 10, wherein the at least one gene sequence from a repetitive element group comprises at least one selected from the group consisting of SAT2CHRM1 SEQ ID NOS:9 and
 21. 15. The method of claim 10, wherein the at least one gene sequence from a maternally imprinted gene group comprises at least one selected from the group consisting of PLAGL1 SEQ ID NOS:7 and 19, MEST SEQ ID NOS:5 and 17, and DIRAS3 SEQ ID NOS:3 and
 15. 16. The method of claim 10, wherein the at least one gene sequence from a non-imprinted gene group comprises at least one selected from the group consisting of HRAS SEQ ID NOS:63 and 20, NTF3 SEQ ID NOS:2 and 14, MT1A SEQ ID NOS:4 and 16, PAX8 SEQ ID NOS:1 and 13, SFN SEQ ID NOS:6 and 18, RNR1 SEQ ID NOS:10 and 22, CYP27B1 SEQ ID NOS:11 and 23 and ICAM1 SEQ ID NOS:12 and
 24. 17. A method for screening for agents that cause spermatogenic deficits, abnormal sperm or abnormal fertility comprising: obtaining human ES-cell derived primordial germ cells; contacting the germ cells or descendants thereof, with at least one test agent; culturing the contacted germ cells or the descendants thereof under conditions suitable for germ cell proliferation or development; obtaining a sample of genomic DNA from the contacted cultured germ cells or the descendants thereof; determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from the group consisting of HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, MEST, RNR1, CYP27B1 and ICAM1; and identifying, based on the methylation status of the at least one CpG sequence, at least one test agent that causes at least one of spermatogenic deficits, abnormal sperm, and abnormal fertility.
 18. The method of claim 17, wherein the determined methylation status of the at least one CpG sequence is hypermethylation.
 19. The method of claim 17, wherein determining the methylation status of at least one CpG dinucleotide sequence comprises treating the genomic DNA, or a fragment thereof, with one or more reagents to convert 5-position unmethylated cytosine bases to uracil or to another base that is detectably dissimilar to cytosine in terms of hybridization properties.
 20. The method of claim 19, wherein treating comprises use of bisulfite treatment of the DNA.
 21. The method of claim 17, wherein the at least one gene sequence is selected from the group consisting of HRAS SEQ ID NOS:63 and 20, NTF3 SEQ ID NOS:2 and 14, MT1A SEQ ID NOS:4 and 16, PAX8 SEQ ID NOS:1 and 13, DIRAS3 SEQ ID NOS:3 and 15, PLAGL1 SEQ ID NOS:7 and 19, SFN SEQ ID NOS:6 and 18, SAT2CHRM1 SEQ ID NOS:9 and 21, MEST SEQ ID NOS:5 and 17, RNR1 SEQ ID NOS:10 and 22, CYP27B1 SEQ ID NOS:11 and 23 and ICAM1 SEQ ID NOS:12 and
 24. 